Design and Implementation of Myoelectric Controlled Arm
- 1 Al Balqa Applied University, Jordan
- 2 Abu Dhabi University, United Arab Emirates
- 3 Staffordshire University, United Kingdom
Abstract
In this study a discrimination system, using a neural network for Electromyogram (EMG) externally controlled Arm is proposed. In this system, the Artificial Neural Network (ANN) is used to learn the relation between the power spectrum of EMG signal analysed by Fast Fourier Transform (FFT) and the performance desired by handicapped people. The Neural Network can discriminate 4 performances of the EMG signals simultaneously. The digital signal processing was realized using MATLAB and LabVIEW software.
DOI: https://doi.org/10.3844/jmrsp.2019.552.562
Copyright: © 2019 Tariq M. Younes, Mohammad A. AlKhedher, Abdel-Hamid Soliman and Aiman Al Alawin. This is an open access article distributed under the terms of the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Electromyogram
- Neural Network
- Biosignal
- Gripping and Rotating